Level of detail control for geostreaming

ABSTRACT

Systems and methods described herein are directed towards controlling a level of detail for geostreaming data. In some examples, an identifying event data that includes location information. A polygon may be defined that comprises points on a map corresponding to the event data. A first level of detail may be determined and a fidelity of the polygon may be changed based at least in part on the first level of detail. Second event data may be received that identifies a location of an object. It may be identified whether the object is within the location information and a user interface may be prepared that presents whether the object is in an affected area.

CROSS-REFERENCE TO RELATED APPLICATION

The present application is a continuation of U.S. application Ser. No.15/993,226, filed May 30, 2018, entitled “LEVEL OF DETAIL CONTROL FORGEOSTREAMING,” which is a continuation of and claims the benefit andpriority of International Application No. PCT/RU2016/000040, filed Feb.1, 2016, the entire contents of which are herein incorporated byreference for all purposes.

BACKGROUND

In traditional database systems, data is stored in one or more databasesusually in the form of tables. The stored data is then queried andmanipulated using a data management language such as a structured querylanguage (SQL). For example, a SQL query may be defined and executed toidentify relevant data from the data stored in the database. A SQL queryis thus executed on a finite set of data stored in the database.Further, when a SQL query is executed, it is executed once on the finitedata set and produces a finite static result. Databases are thus bestequipped to run queries over finite stored data sets. A number of modernapplications and systems however generate data in the form of continuousdata or event streams instead of a finite data set. Examples of suchapplications include but are not limited to sensor data applications,financial tickers, network performance measuring tools (e.g. networkmonitoring and traffic management applications), clickstream analysistools, automobile traffic monitoring, and the like. Such applicationshave given rise to a need for a new breed of applications that canprocess the data streams. For example, a temperature sensor may beconfigured to send out temperature readings. Managing and processingdata for these types of event stream-based applications involvesbuilding data management and querying capabilities with a strongtemporal focus. A different kind of querying mechanism is needed thatcomprises long-running queries over continuous unbounded sets of data.While some vendors now offer product suites geared towards event streamsprocessing, these product offerings still lack the processingflexibility required for handling today's events processing needs.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a simplified block diagram illustrating an examplearchitecture for implementing the features described herein, accordingto some embodiments.

FIG. 2 is a simplified block diagram illustrating at least some featuresof an event processing engine capable of handling continuous streams ofdata as described herein, according to at least one example.

FIG. 3 is another simplified block diagram illustrating an examplegeofence as described herein, according to some embodiments.

FIG. 4 is a simplified block diagram illustrating an examplearchitecture for implementing the test data generation as describedherein, according to some embodiments.

FIG. 5 is a simplified block diagram illustrating an examplerepresentation for implementing the test data generation as describedherein, according to some embodiments.

FIG. 6 is a simplified block diagram illustrating an examplearchitecture for implementing the level of detail control as describedherein, according to some embodiments.

FIG. 7 is a simplified block diagram illustrating an examplerepresentation for implementing the level of detail control as describedherein, according to some embodiments.

FIG. 8 is a simplified block diagram illustrating an example flow forimplementing the test data generation as described herein, according tosome embodiments.

FIG. 9 is a simplified block diagram illustrating an example flow forimplementing the level of detail control as described herein, accordingto some embodiments.

FIG. 10 is a simplified block diagram illustrating a distributed systemfor implementing some of the examples described herein, according to atleast one example.

FIG. 11 is a simplified block diagram illustrating components of asystem environment by which services provided by the components of anembodiment system may be offered as cloud services, in accordance withsome of the examples described herein, according to at least oneexample.

FIG. 12 is a simplified block diagram illustrating an example computersystem, in which various embodiments of the present disclosure may beimplemented in accordance with some of the examples described herein,according to at least one example.

DETAILED DESCRIPTION

In applications such as stock quote monitoring, automobile trafficmonitoring, and data sensing, data is generated in the form of a streamof events over time. A data stream, also referred to as an event stream,is a real-time, continuous, sequence of events. Examples of sources thatgenerate data streams include sensors and probes (e.g., radio frequencyidentification (RFID) sensors, temperature sensors, etc.) configured tosend a sequence of sensor readings, financial tickers, networkmonitoring and traffic management applications sending network status,click stream analysis tools, and others. The term “events” are usedinterchangeably with “tuples.” As used herein, tuples of a stream havethe same set of attributes but not necessarily the same attribute valuesfor those attributes. Each tuple is also associated with a particulartime. A tuple may be considered to be logically similar to a single rowor record in a relational database.

In applications such as fleet management, data is in the form ofcontinuous data streams. The continuous data stream may be a stream ofdata that arrives at a stream processing server with no explicit endrange. By processing the continuous data streams, applications candetect complex patterns, event correlations, and relationships betweenevents. For example, a continuous data stream might have informationabout automobiles that pass a particular area (e.g., a state, county, orcountry) where there are significant weather and/or traffic incidents.An automobile can send coordinates continuously. Based upon this datastream, problems such as detecting if an automobile is in the proximityof the certain area of interest such as a traffic accident or severeweather condition can be solved.

Spatial data support in traditional database systems and data processingalgorithms are designed to process spatial data stored as finite storeddata sets. Traditional database systems store data in database tableswhere the data may be queried and manipulated using a data managementlanguage such as the Structured Query Language (SQL). Databasemanagement systems and algorithms are unable to handle continuous datastreams of geometries because they are designed based upon theassumption that the system stores a large, but finite, collection ofdata. Geostreaming with a complex event processor (CEP) can be used tohandle continuous data streams that include geospatial information.

In developing Geostreaming applications using CEP, it requirespositional information in order to create and test applications.Typically, the positional information is created manually in the textualform such as a Comma Separated Values (CSV) file or a JavaScript ObjectNotation (JSON) file, using a manual process as follows:

-   Load the reference polygons into a map.-   Find the locations of interesting events.-   Get the longitudes and latitudes of the locations.-   Save the longitudes and latitudes into a text format.

However, this process is very time consuming especially with creatingthe time series relations between the locations. Some geostreamingapplications require analyzing time series relations between thelocations (for example, extended stay in the hazardous area).

Additionally, with geostreaming applications, polygon types aregenerally used to represent surroundings or moving objects. If thepolygon has many vertices, such as polygon representing a whole UnitedStates (US) state, the point operations against polygon could be veryheavy and could affect the scalability and performance of the CEPserver. The typical solution of this problem is to use clustering andadd more servers.

In some examples, the solution may be built within a CEP component(e.g., a spatial cartridge component) that handles geostreaming. Forpattern-based test data generation, the “pattern” concept may be used inorder to abstract the complex applications and allows users to createapplications with only providing several parameters. In some examples,for geostreaming applications, the pattern may include a Geofence, anin-route and/or out-of-route, and/or moving object tracking. Since thepattern abstracts the complex algorithm, it may be known what the testdata should look like in order to drive the algorithm. For the abovegeostreaming patterns, the required test data are:

-   Geofence: a path/route information crossing the polygon representing    the virtual surrounding.-   In-route/Out-of-route: a deviated path/route information from the    original route information.-   Moving object tracking: multiple path/route information which cross    each other to simulate interactions of objects.

Here, the test data generator concept may be introduced for eachpattern. The test generator is used by the CEP component whenapplications are created from a pattern. One example implementation oftest data generator for Geofence pattern works as follows:

-   The reference polygon representing the virtual surrounding is fed    into the test generator-   The test generator has several control parameters that a user can    provide:    -   a. start Distance: how far the test generator starts from the        reference polygons    -   b. distanceStep, frequency: how often the test generator sends        the test location    -   c. pathProvider: simple line, the actual routing, the actual        flight/ship path-   The test generator first selects two points based on the input    polygon and startDistance.-   Linestring(s) between two points are creating using pathProvider,    either simple line, or routing between two points, or the    flight/ship path.-   The test generator creates points on the linestring(s) with    distanceStep and frequency information. The geodesic interpolation    operation is performed while creating points on the linestring(s).-   The created points are fed to the processor as the position stream.

Some of pattern has the time series relation concept such as stay in thearea in the geofence, extended out-of-route. The test generator cansimulate such time series relation in creating points on thelinestring(s).

As noted, the solution may be built within a CEP component (e.g., aspatial cartridge component) that handles geostreaming. For level ofdetail control, the typical operations may include:

-   Checking if a moving object is within the distance of virtual fence    around some area; and-   Checking if a moving object is actually in the virtual fence.

For the above operations, typically the polygons are stored in relation(e.g., in a relational database) and also in the spatial index. In someexmaples, the CEP component may use a two-step query model, thatincludes:

-   Querying against spatial index to locate the polygons; and-   Pointing operations such as withinDistance or inside between    geometries.

Based at least in part on the context and application, the polygons thatrepresent the virtual fence or the moving object does not need to beexact with the actual geometries. For most of the geostreamingapplications, the polygons can be approximates of the actual geometries.The level of detail in three-dimensional (3D) computer graphics involvesdecreasing the complexity of a 3D object representation as it moves awayfrom the viewer or according to other metrics such as object importance,speed or position.

In some cases, a polygon simplification algorithm may be used inreducing the complexities of polygons. The algorithm works as follows inreducing the complexities of polygons:

-   On loading geometries to relation, the level of simplification is    decided using the proximity parameter and the current complexity of    polygons.-   On visualizing geometries in the map, different level of    simplification is applied using the zoom level of map. The output of    simplified geometries can be cached and reused.

For dynamic level of detail based on the proximity parameter, most ofthe geostreaming operations have a proximity parameter (e.g.,withinDistance operation requires the distance from the virtualsurrounding).

In some exmaples, the service provider may be configured to calculatethe bounding box of the received polygon. Then, the service provider maycalculate the horizontal and vertical distances in meters. The followingequation may be utilized to determine the fidelity:

F=(x*y/p*p)*s

-   where, F: simplification factor 0-100 (0 is the exact    representation)-   s=scale factor:default is 50-   x, y:bounding box of the polygon-   p:proximity parameter

The level of detail based on the zoom level may be calculated using thefollowing equations:

-   Z: Zoom level (0-100) 100: maximum zoom level-   s: scale factor-   F=(1−z/s)*100

The techniques described above and below may be implemented in a numberof ways and in a number of contexts. Several example implementations andcontexts are provided with reference to the following figures, asdescribed below in more detail. However, the following implementationsand contexts are but a few of many.

FIG. 1 depicts a simplified example system or architecture 100 in whichtechniques for implementing a pattern-based automated test datageneration system and/or a level of detail control system may beimplemented. In architecture 100, one or more users 102 (e.g., accountholders) may utilize user computing devices 104(1)-(N) (collectively,“user devices 104”) to access one or more service provider computers 106via one or more networks 108. In some aspects, the service providercomputers 106 may also be in communication with one or more streamingdata source computers 110 and/or one or more databases 112 via thenetworks 108. For example, the users 102 may utilize the serviceprovider computers 106 to access or otherwise manage data of thestreaming data source computers 110 and/or the databases 112 (e.g.,queries may be run against either or both of 110, 112). The databases112 may be relational databases, SQL servers, or the like and may, insome examples, manage historical data, event data, relations, archivedrelations, or the like on behalf of the users 102. Additionally, thedatabases 112 may receive or otherwise store data provided by thestreaming data source computers 110. In some examples, the users 102 mayutilize the user devices 104 to interact with the service providercomputers 106 by providing queries (also referred to as “querystatements”) or other requests for data (e.g., historical event data,streaming event data, etc.). Such queries or requests may then beexecuted by the service provider computers 106 to process data of thedatabases 112 and/or incoming data from the streaming data sourcecomputers 110. Further, in some examples, the streaming data sourcecomputers 110 and/or the databases 112 may be part of an integrated,distributed environment associated with the service provider computers106.

In some examples, the networks 108 may include any one or a combinationof multiple different types of networks, such as cable networks, theInternet, wireless networks, cellular networks, intranet systems, and/orother private and/or public networks. While the illustrated examplerepresents the users 102 accessing the service provider computers 106over the networks 108, the described techniques may equally apply ininstances where the users 102 interact with one or more service providercomputers 106 via the one or more user devices 104 over a landlinephone, via a kiosk, or in any other manner. It is also noted that thedescribed techniques may apply in other client/server arrangements(e.g., set-top boxes, etc.), as well as in non-client/serverarrangements (e.g., locally stored applications, etc.).

The user devices 104 may be any type of computing device such as, butnot limited to, a mobile phone, a smart phone, a personal digitalassistant (PDA), a laptop computer, a desktop computer, a thin-clientdevice, a tablet PC, etc. In some examples, the user devices 104 may bein communication with the service provider computers 106 via thenetworks 108, or via other network connections. Further, the userdevices 104 may also be configured to provide one or more queries orquery statements for requesting data of the databases 112 (or other datastores) to be processed.

In some aspects, the service provider computers 106 may also be any typeof computing devices such as, but not limited to, mobile, desktop,thin-client, and/or cloud computing devices, such as servers. In someexamples, the service provider computers 106 may be in communicationwith the user devices 104 via the networks 108, or via other networkconnections. The service provider computers 106 may include one or moreservers, perhaps arranged in a cluster, as a server farm, or asindividual servers not associated with one another. These servers may beconfigured to perform or otherwise host features described hereinincluding, but not limited to, the management of archived relations,configurable data windows associated with archived relations, and/oraccurately counting change events associated with managing archivedrelations described herein. Additionally, in some aspects, the serviceprovider computers 106 may be configured as part of an integrated,distributed computing environment that includes the streaming datasource computers 110 and/or the databases 112.

In one illustrative configuration, the service provider computers 106may include at least one memory 136 and one or more processing units (orprocessor(s)) 138. The processor(s) 138 may be implemented asappropriate in hardware, computer-executable instructions, firmware, orcombinations thereof. Computer-executable instruction or firmwareimplementations of the processor(s) 138 may include computer-executableor machine-executable instructions written in any suitable programminglanguage to perform the various functions described.

The memory 136 may store program instructions that are loadable andexecutable on the processor(s) 138, as well as data generated during theexecution of these programs. Depending on the configuration and type ofservice provider computers 106, the memory 136 may be volatile (such asrandom access memory (RAM)) and/or non-volatile (such as read-onlymemory (ROM), flash memory, etc.). The service provider computers 106 orservers may also include additional storage 140, which may includeremovable storage and/or non-removable storage. The additional storage140 may include, but is not limited to, magnetic storage, optical disks,and/or tape storage. The disk drives and their associatedcomputer-readable media may provide non-volatile storage ofcomputer-readable instructions, data structures, program modules, andother data for the computing devices. In some implementations, thememory 136 may include multiple different types of memory, such asstatic random access memory (SRAM), dynamic random access memory (DRAM),or ROM.

The memory 136, the additional storage 140, both removable andnon-removable, are all examples of computer-readable storage media. Forexample, computer-readable storage media may include volatile ornon-volatile, removable or non-removable media implemented in any methodor technology for storage of information such as computer-readableinstructions, data structures, program modules, or other data. Thememory 136 and the additional storage 140 are all examples of computerstorage media.

The service provider computers 106 may also contain communicationsconnection(s) 142 that allow the identity interface computers 120 tocommunicate with a stored database, another computing device or server,user terminals, and/or other devices on the networks 108. The serviceprovider computers 106 may also include input/output (I/O) device(s)144, such as a keyboard, a mouse, a pen, a voice input device, a touchinput device, a display, one or more speakers, a printer, etc.

Turning to the contents of the memory 136 in more detail, the memory 136may include an operating system 146 and one or more application programsor services for implementing the features disclosed herein including atleast a test data generation module 148 and a level of detail controlmodule 150. As used herein, modules may refer to programming modulesexecuted by servers or clusters of servers that are part of a service.In this particular context, the modules may be executed by the serversor clusters of servers that are part of the service provider computers106.

In some examples, the test data generation module 148 may be configuredto receive, from an application, a reference polygon that identifies ageographic region on a map; receive, from the application, a controlparameter associated with a route on the map; select at least two pointson the map based at least in part on the reference polygon and thecontrol parameter; generate a path from a first point of the at leastone points to a second point of the at least two points; create pointson the path based at least in part on at least one of distanceinformation between the first point and the second point or frequencyinformation between the first point and the second point; generate testdata for the application by processing the points on the path; andprovide the test data to the application.

In some examples, the level of detail control module 150 may beconfigured to identify first event data of a first event source, thefirst event data comprising location information for an affected area ofa map; define a polygon comprising points on the map that correspond toat least a subset of each entry of the first event data; determine afirst level of detail for processing the first event data based at leastin part on context information; change a fidelity of the polygon byadjusting a number of the points of the polygon based at least in parton the first level of detail; receive second event data from a secondevent source, the second event data comprising position information foran object; identify whether the object is within the affected area basedat least in part on a determination of whether the position informationmatches the points of the polygon; and prepare a user interface forpresenting whether the object is within the affected area based at leastin part on a second level of detail.

FIG. 2 depicts a simplified high level diagram of an event processingsystem 200 that may incorporate an embodiment of the present disclosure.Event processing system 200 may comprise one or more event sources (204,206, 208), an event processing server (EPS) 202 (also referred to as CQService 202) that is configured to provide an environment for processingevent streams, and one or more event sinks (210, 212). The event sourcesgenerate event streams that are received by EPS 202. EPS 202 may receiveone or more event streams from one or more event sources. For example,as shown in FIG. 2, EPS 202 receives an input event stream 214 fromevent source 204, a second input event stream 216 from event source 206,and a third event stream 218 from event source 208. One or more eventprocessing applications (220, 222, and 224) may be deployed on and beexecuted by EPS 202. An event processing application executed by EPS 202may be configured to listen to one or more input event streams, processthe events received via the one or more event streams based uponprocessing logic that selects one or more events from the input eventstreams as notable events. The notable events may then be sent to one ormore event sinks (210, 212) in the form of one or more output eventstreams. For example, in FIG. 2, EPS 202 outputs an output event stream226 to event sink 210, and a second output event stream 228 to eventsink 212. In certain embodiments, event sources, event processingapplications, and event sinks are decoupled from each other such thatone can add or remove any of these components without causing changes tothe other components.

In one embodiment, EPS 202 may be implemented as a Java servercomprising a lightweight Java application container, such as one basedupon Equinox OSGi, with shared services. In some embodiments, EPS 202may support ultra-high throughput and microsecond latency for processingevents, for example, by using JRockit Real Time. EPS 202 may alsoprovide a development platform (e.g., a complete real time end-to-endJava Event-Driven Architecture (EDA) development platform) includingtools (e.g., Oracle CEP Visualizer and Oracle CEP IDE) for developingevent processing applications.

An event processing application is configured to listen to one or moreinput event streams, execute logic (e.g., a query) for selecting one ormore notable events from the one or more input event streams, and outputthe selected notable events to one or more event sources via one or moreoutput event streams. FIG. 2 provides a drilldown for one such eventprocessing application 220. As shown in FIG. 2, event processingapplication 220 is configured to listen to input event stream 218,execute a query 230 comprising logic for selecting one or more notableevents from input event stream 218, and output the selected notableevents via output event stream 228 to event sink 212. Examples of eventsources include, without limitation, an adapter (e.g., JMS, HTTP, andfile), a channel, a processor, a table, a cache, and the like. Examplesof event sinks include, without limitation, an adapter (e.g., JMS, HTTP,and file), a channel, a processor, a cache, and the like.

Although event processing application 220 in FIG. 2 is shown aslistening to one input stream and outputting selected events via oneoutput stream, this is not intended to be limiting. In alternativeembodiments, an event processing application may be configured to listento multiple input streams received from one or more event sources,select events from the monitored streams, and output the selected eventsvia one or more output event streams to one or more event sinks. Thesame query can be associated with more than one event sink and withdifferent types of event sinks.

Due to its unbounded nature, the amount of data that is received via anevent stream is generally very large. Consequently, it is generallyimpractical and undesirable to store or archive all the data forquerying purposes. The processing of event streams requires processingof the events in real time as the events are received by EPS 202 withouthaving to store all the received events data. Accordingly, EPS 202provides a special querying mechanism that enables processing of eventsto be performed as the events are received by EPS 202 without having tostore all the received events.

Event-driven applications are rule-driven and these rules may beexpressed in the form of continuous queries that are used to processinput streams. A continuous query may comprise instructions (e.g.,business logic) that identify the processing to be performed forreceived events including what events are to be selected as notableevents and output as results of the query processing. Continuous queriesmay be persisted to a data store and used for processing input streamsof events and generating output streams of events. Continuous queriestypically perform filtering and aggregation functions to discover andextract notable events from the input event streams. As a result, thenumber of outbound events in an output event stream is generally muchlower than the number of events in the input event stream from which theevents are selected.

Unlike a SQL query that is run once on a finite data set, a continuousquery that has been registered by an application with EPS 202 for aparticular event stream may be executed each time that an event isreceived in that event stream. As part of the continuous queryexecution, EPS 202 evaluates the received event based upon instructionsspecified by the continuous query to determine whether one or moreevents are to be selected as notable events, and output as a result ofthe continuous query execution.

The continuous query may be programmed using different languages. Incertain embodiments, continuous queries may be configured using the CQLprovided by Oracle Corporation and used by Oracle's Complex EventsProcessing (CEP) product offerings. Oracle's CQL is a declarativelanguage that can be used to program queries (referred to as CQLqueries) that can be executed against event streams. In certainembodiments, CQL is based upon SQL with added constructs that supportprocessing of streaming events data.

In one embodiment, an event processing application may be composed ofthe following component types:

-   (1) One or more adapters that interface directly to the input and    output stream and relation sources and sinks. Adapters are    configured to understand the input and output stream protocol, and    are responsible for converting the event data into a normalized form    that can be queried by an application processor. Adapters may    forward the normalized event data into channels or output streams    and relation sinks. Event adapters may be defined for a variety of    data sources and sinks.-   (2) One or more channels that act as event processing endpoints.    Among other things, channels are responsible for queuing event data    until the event processing agent can act upon it.-   (2) One or more application processors (or event processing agents)    are configured to consume normalized event data from a channel,    process it using queries to select notable events, and forward (or    copy) the selected notable events to an output channel.-   (4) One or more beans are configured to listen to the output    channel, and are triggered by the insertion of a new event into the    output channel. In some embodiments, this user code is a    plain-old-Java-object (POJO). The user application can make use of a    set of external services, such as JMS, Web services, and file    writers, to forward the generated events to external event sinks.-   (5) Event beans may be registered to listen to the output channel,    and are triggered by the insertion of a new event into the output    channel. In some embodiments, this user code may use the Oracle CEP    event bean API so that the bean can be managed by Oracle CEP.

In one embodiment, an event adapter provides event data to an inputchannel. The input channel is connected to a CQL processor associatedwith one or more CQL queries that operate on the events offered by theinput channel. The CQL processor is connected to an output channel towhich query results are written.

In some embodiments, an assembly file may be provided for an eventprocessing application describing the various components of the eventprocessing application, how the components are connected together, andevent types processed by the application. Separate files may be providedfor specifying the continuous query or business logic for selection ofevents.

It should be appreciated that system 200 depicted in FIG. 2 may haveother components than those depicted in FIG. 2. Further, the embodimentshown in FIG. 2 is only one example of a system that may incorporate anembodiment of the present disclosure. In some other embodiments, system200 may have more or fewer components than shown in FIG. 2, may combinetwo or more components, or may have a different configuration orarrangement of components. System 200 can be of various types includinga personal computer, a portable device (e.g., a mobile telephone ordevice), a workstation, a network computer, a mainframe, a kiosk, aserver, or any other data processing system. In some other embodiments,system 200 may be configured as a distributed system where one or morecomponents of system 200 are distributed across one or more networks inthe cloud.

The one or more of the components depicted in FIG. 2 may be implementedin software, in hardware, or combinations thereof. In some embodiments,the software may be stored in memory (e.g., a non-transitorycomputer-readable medium), on a memory device, or some other physicalmemory and may be executed by one or more processing units (e.g., one ormore processors, one or more processor cores, one or more GPUs, etc.).

Illustrative methods and systems for implementing the test datageneration systems and level of detail control systems are describedabove. Some or all of these systems and methods may, but need not, beimplemented at least partially by architectures and processes such asthose shown at least in FIGS. 1-2 above.

FIG. 3 depicts a simplified diagram of geofence 300. The geofence is oneform of location based service that acts as a virtual barrier. Thegeofence can be either a circle around a point location or a set ofboundaries. The geofence may be circular, rectangular, polygonal, and/ormulti-polygonal. The primary events that are to be processed and/ortracked with respect to the geofence 300 are when an entity (user,computing device, etc.) enters the geofence 300, exits the geofence 300,or stays (dwells) within the geofence.

Some types of geostreaming include the tracking of moving objects andthe generation of events. What can be tracked with moving objectsinclude speed, direction, proximity to stationary object, proximity toother moving objects, if moving objects is in-route or out-of-route frompre-defined path. Among these, proximity to other events is interestingas it's a kind of derived event from a primary event. One example ofsuch case is a distance to a congested area if the congested area is anevent calculated from a spatial aggregation.

FIG. 4 is a simplified block diagram illustrating an examplearchitecture 400 for implementing the test data generation describedherein. In some examples, a Representational State Transfer (REST)source 402 may provide streaming data to the CEP component (e.g., aspatial cartridge). The streaming data may in the form of HyperTextTransfer Protocol (http) or Extensible Markup Language (XML) documents.In some exmaples, the source may actually be a Rich Site Summary (RSS)feed such as, but not limited to, one from the National Weather Service(NWS) or the like. The source data may be processed by a FenceRelationmodule 404 and/or a test position generator 406. The test positiongenerator 406 may be configured to provide results to a position stream408 which can, in turn, provide its results to a geofence processor 410.Similarly, results from the fence relation 404 may go to the geofenceprocessor 410. Final results from the geofence processors 410 may beprovided to an output visualization module 422.

In some examples, typical position generation may include:

-   Static Source from CSV, DB    -   a. Cannot run with dynamic fences    -   b. Hard to create complex scenarios-   Full Simulator    -   a. Need too much resource to develop    -   b. Can make complex scenarios

Additionally, the TestPathGenerator may include automatic generation oftest positions from geofences.

Additionally, the TestPosGenerator may include:

-   Delay-   Step-   PathProvider    -   a. GeometryCutPathProvider    -   b. TruckPathProvider    -   c. FlightPathProvider

A geometry cut path provider may:

-   Generate a line which cuts geometries with properties of:    -   startDistance    -   distanceStep-   A route provider may:-   setup ‘routeProvider’ to create actual route using the road data    -   a. simplifyThreshold    -   b. routeProivder

A flight path provider may utilize an airport database (e.g., fromopenflights.org or other sites), may select two airports, and/or maycreate a geodesic path. Additionally, a routing engine may include aRouteProvider interface.

FIG. 5 is a simplified block diagram illustrating an examplerepresentation 500 for implementing the test data generation describedherein. In FIG. 5, the representation 500 is of a polygon (e.g., an areaaffected by inclement weather, a county, a sub-region, etc.) thathappens to be located in Montana. The polygon data may be received by astream of weather data or the like and may change as new locationinformation is received (e.g., in a stream). For example, if weatherdata is received from the NWS, the weather data may indicate an areaaffected by a storm. The points of the polygon may be received by theNWS data (e.g., in an RSS feed). Data points of the polygon may bestored in a relational database and plotted on the representation (map)500 of FIG. 5. Additionally, two points may be received from anapplication (e.g., a mobile map/weather application) that intends totest out its own use of the polygon information. A geofence processor(e.g., 410 of FIG. 4) or the like may be utilized to plot the two pointson the map. These two points can simulate a user (e.g., truck or othervehicle) traveling through the affected area that is represented by thepolygon. Once other information (e.g., route, speed, etc.) is received,a straight line (or other type of line) can be generated between the twopoints. Speed information can then be utilized to determine additionalpoints along the line between the in-route and out-of-route points (thetwo initial points). This data is the test data, generated by thissystem, and is provided back to the application. The application canthen determine whether it is working properly or will be able to processthe incoming data properly.

FIG. 6 is a simplified block diagram illustrating an examplearchitecture 600 for implementing the level of detail control asdescribed herein. Similar to FIG. 5, a REST source may provide polygoninformation for an affected area or for any geofence application. Insome examples, the information may be parsed and/or converted from eventformat to tuple format. A first level of detail control may bedetermined (e.g., using a first algorithm) to reduce the fidelity of thepolygon. This is the input level of control. This data may be passed tothe fence relation module. Additionally, position information from oneor more entities (e.g., trucks, users, etc.) may be received andprocessed by a position stream processor. A spatial join may then beperformed, where the polygon information from the fence relation may bejoined with the spatial information (e.g., the position info fromtrucks). A geofence processor may perform the joining of the data, andan output visualizer may prepare the joined data for visualization. Onceprepared, a second level of detail control (e.g., using a differentalgorithm) may be utilized to increase or decrease the fidelity of thedata to visualized based at least in part on a zoom level. The zoomlevel may be configured by a user as they review the visualization.

FIG. 7 is a simplified block diagram illustrating an examplerepresentation 700 for implementing the level of detail control asdescribed herein. In this figure, it is shown that the data may bereceived at a first fidelity (e.g., 651 points for the polygon), butthen the level of detail may be changed (e.g., reduced) in order toenable faster (less processor-intensive) calculation of whether trucksentering the area are going to intersect with the polygon. Only once itis determined that a truck is near to the polygon, does the system needto have a higher fidelity. Additionally, once a truck is within thepolygon, a much lower fidelity may be used, thus further reducing theamount processing power required to perform the calculations. In someexamples, the spatial cartridge may perform the majority of theprocessing at a fairly low fidelity. For visualization, the fidelity maybe increased based at least in part on the zoom level of the user. Forexample, if the user attempts to zoom in closer, the fidelity will needto be increased. However, if the user is zoomed out relatively far, thefidelity can remain relatively low.

FIGS. 8 and 9 are flow diagrams of processes for implementing systemsand methods described herein, in accordance with at least someembodiments. The processes are illustrated as logical flow diagrams,each operation of which represents a sequence of operations that can beimplemented in hardware, computer instructions, or a combinationthereof. In the context of computer instructions, the operationsrepresent computer-executable instructions stored on one or morecomputer-readable storage media that, when executed by one or moreprocessors, perform the recited operations. Generally, computerexecutable instructions include routines, programs, objects, components,data structures and the like that perform particular functions orimplement particular data types. The order in which the operations aredescribed is not intended to be construed as a limitation, and anynumber of the described operations can be combined in any order and/orin parallel to implement the processes.

Additionally, some, any, or all of the process (or any other processesdescribed herein, or variations and/or combinations thereof) may beperformed under the control of one or more computer systems configuredwith executable instructions and may be implemented as code (e.g.,executable instructions, one or more computer programs or one or moreapplications) executing collectively on one or more processors, byhardware or combinations thereof. As noted above, the code may be storedon a computer-readable storage medium, for example, in the form of acomputer program comprising a plurality of instructions executable byone or more processors. The computer-readable storage medium may benon-transitory.

In some examples, the one or more service provider computers 106 (e.g.,utilizing at least the test data generation module 148 and/or the levelof detail control module 150 shown in FIG. 1 may perform the processes800 and 900 of FIGS. 8 and 9, respectively. In FIG. 8, the process 800may include receiving, from an application, a reference polygon thatidentifies a geographic region on a map at 802; receiving, from theapplication, a control parameter associated with a route on the map at804; selecting at least two points on the map based at least in part onthe reference polygon and the control parameter at 806; generating apath from a first point of the at least one points to a second point ofthe at least two points at 808; creating points on the path based atleast in part on at least one of distance information between the firstpoint and the second point or frequency information between the firstpoint and the second point at 810; generating test data for theapplication by processing the points on the path at 812; and providingthe test data to the application at 814.

In FIG. 9, the process 900 may include identifying first event data of afirst event source, the first event data comprising location informationfor an affected area of a map at 902; defining a polygon comprising apoint on the map for at least a subset of each entry of the first eventdata at 904; determining a number of points of the polygon at 906;receiving second event data from a second event source, the second eventdata comprising position information for an entity located at a physicallocation represented by the map at 908; determining a first level ofdetail for processing the first event data based at least in part oncontext information associated with the map or the entity at 910;changing a fidelity of the polygon by adjusting the number of points ofthe polygon based at least in part on the first level of detail at 912;joining the second event data with adjusted polygon information thatcorresponds to the adjusted number of points of the polygon to determinewhether the position information matches the adjusted polygoninformation at 914; identifying whether the entity is within theaffected area based at least in part on the determination of whether theposition information matches the adjusted polygon information at 916;and preparing a user interface for presenting whether the entity iswithin the affected area based at least in part on a second level ofdetail at 918.

FIG. 10 depicts a simplified diagram of a distributed system 1000 forimplementing one of the embodiments. In the illustrated embodiment,distributed system 1000 includes one or more client computing devices1002, 1004, 1006, and 1008, which are configured to execute and operatea client application such as a web browser, proprietary client (e.g.,Oracle Forms), or the like over one or more network(s) 1010. Server 1012may be communicatively coupled with remote client computing devices1002, 1004, 1006, and 1008 via network 1010.

In various embodiments, server 1012 may be adapted to run one or moreservices or software applications provided by one or more of thecomponents of the system. The services or software applications caninclude non-virtual and virtual environments. Virtual environments caninclude those used for virtual events, tradeshows, simulators,classrooms, shopping exchanges, and enterprises, whether two- orthree-dimensional (3D) representations, page-based logical environments,or otherwise. In some embodiments, these services may be offered asweb-based or cloud services or under a Software as a Service (SaaS)model to the users of client computing devices 1002, 1004, 1006, and/or1008. Users operating client computing devices 1002, 1004, 1006, and/or1008 may in turn utilize one or more client applications to interactwith server 1012 to utilize the services provided by these components.

In the configuration depicted in the figure, the software components1018, 1020 and 1022 of system 1000 are shown as being implemented onserver 1012. In other embodiments, one or more of the components ofsystem 1000 and/or the services provided by these components may also beimplemented by one or more of the client computing devices 1002, 1004,1006, and/or 1008. Users operating the client computing devices may thenutilize one or more client applications to use the services provided bythese components. These components may be implemented in hardware,firmware, software, or combinations thereof. It should be appreciatedthat various different system configurations are possible, which may bedifferent from distributed system 1000. The embodiment shown in thefigure is thus one example of a distributed system for implementing anembodiment system and is not intended to be limiting.

Client computing devices 1002, 1004, 1006, and/or 1008 may be portablehandheld devices (e.g., an iPhone®, cellular telephone, an iPad®,computing tablet, a personal digital assistant (PDA)) or wearabledevices (e.g., a Google Glass® head mounted display), running softwaresuch as Microsoft Windows Mobile®, and/or a variety of mobile operatingsystems such as iOS, Windows Phone, Android, BlackBerry 8, Palm OS, andthe like, and being Internet, e-mail, short message service (SMS),Blackberry®, or other communication protocol enabled. The clientcomputing devices can be general purpose personal computers including,by way of example, personal computers and/or laptop computers runningvarious versions of Microsoft Windows®, Apple Macintosh®, and/or Linuxoperating systems. The client computing devices can be workstationcomputers running any of a variety of commercially-available UNIX® orUNIX-like operating systems, including without limitation the variety ofGNU/Linux operating systems, such as for example, Google Chrome OS.Alternatively, or in addition, client computing devices 1002, 1004,1006, and 1008 may be any other electronic device, such as a thin-clientcomputer, an Internet-enabled gaming system (e.g., a Microsoft Xboxgaming console with or without a Kinect® gesture input device), and/or apersonal messaging device, capable of communicating over network(s)1010.

Although exemplary distributed system 1000 is shown with four clientcomputing devices, any number of client computing devices may besupported. Other devices, such as devices with sensors, etc., mayinteract with server 1012.

Network(s) 1010 in distributed system 1000 may be any type of networkfamiliar to those skilled in the art that can support datacommunications using any of a variety of commercially-availableprotocols, including without limitation TCP/IP (transmission controlprotocol/Internet protocol), SNA (systems network architecture), IPX(Internet packet exchange), AppleTalk, and the like. Merely by way ofexample, network(s) 1010 can be a local area network (LAN), such as onebased on Ethernet, Token-Ring and/or the like. Network(s) 1010 can be awide-area network and the Internet. It can include a virtual network,including without limitation a virtual private network (VPN), anintranet, an extranet, a public switched telephone network (PSTN), aninfra-red network, a wireless network (e.g., a network operating underany of the Institute of Electrical and Electronics (IEEE) 1002.11 suiteof protocols, Bluetooth®, and/or any other wireless protocol); and/orany combination of these and/or other networks.

Server 1012 may be composed of one or more general purpose computers,specialized server computers (including, by way of example, PC (personalcomputer) servers, UNIX® servers, mid-range servers, mainframecomputers, rack-mounted servers, etc.), server farms, server clusters,or any other appropriate arrangement and/or combination. Server 1012 caninclude one or more virtual machines running virtual operating systems,or other computing architectures involving virtualization. One or moreflexible pools of logical storage devices can be virtualized to maintainvirtual storage devices for the server. Virtual networks can becontrolled by server 1012 using software defined networking. In variousembodiments, server 1012 may be adapted to run one or more services orsoftware applications described in the foregoing disclosure. Forexample, server 1012 may correspond to a server for performingprocessing described above according to an embodiment of the presentdisclosure.

Server 1012 may run an operating system including any of those discussedabove, as well as any commercially available server operating system.Server 1012 may also run any of a variety of additional serverapplications and/or mid-tier applications, including HTTP (hypertexttransport protocol) servers, FTP (file transfer protocol) servers, CGI(common gateway interface) servers, JAVA® servers, database servers, andthe like. Exemplary database servers include without limitation thosecommercially available from Oracle, Microsoft, Sybase, IBM(International Business Machines), and the like.

In some implementations, server 1012 may include one or moreapplications to analyze and consolidate data feeds and/or event updatesreceived from users of client computing devices 1002, 1004, 1006, and1008. As an example, data feeds and/or event updates may include, butare not limited to, Twitter® feeds, Facebook® updates or real-timeupdates received from one or more third party information sources andcontinuous data streams, which may include real-time events related tosensor data applications, financial tickers, network performancemeasuring tools (e.g., network monitoring and traffic managementapplications), clickstream analysis tools, automobile trafficmonitoring, and the like. Server 1012 may also include one or moreapplications to display the data feeds and/or real-time events via oneor more display devices of client computing devices 1002, 1004, 1006,and 1008.

Distributed system 1000 may also include one or more databases 1014 and1016. Databases 1014 and 1016 may reside in a variety of locations. Byway of example, one or more of databases 1014 and 1016 may reside on anon-transitory storage medium local to (and/or resident in) server 1012.Alternatively, databases 1014 and 1016 may be remote from server 1012and in communication with server 1012 via a network-based or dedicatedconnection. In one set of embodiments, databases 1014 and 1016 mayreside in a storage-area network (SAN). Similarly, any necessary filesfor performing the functions attributed to server 1012 may be storedlocally on server 1012 and/or remotely, as appropriate. In one set ofembodiments, databases 1014 and 1016 may include relational databases,such as databases provided by Oracle, that are adapted to store, update,and retrieve data in response to SQL-formatted commands.

FIG. 11 is a simplified block diagram of one or more components of asystem environment 1100 by which services provided by one or morecomponents of an embodiment system may be offered as cloud services, inaccordance with an embodiment of the present disclosure. In theillustrated embodiment, system environment 1100 includes one or moreclient computing devices 1104, 1106, and 1108 that may be used by usersto interact with a cloud infrastructure system 1102 that provides cloudservices. The client computing devices may be configured to operate aclient application such as a web browser, a proprietary clientapplication (e.g., Oracle Forms), or some other application, which maybe used by a user of the client computing device to interact with cloudinfrastructure system 1102 to use services provided by cloudinfrastructure system 1102.

It should be appreciated that cloud infrastructure system 1102 depictedin the figure may have other components than those depicted. Further,the embodiment shown in the figure is only one example of a cloudinfrastructure system that may incorporate an embodiment of thedisclosure. In some other embodiments, cloud infrastructure system 1102may have more or fewer components than shown in the figure, may combinetwo or more components, or may have a different configuration orarrangement of components.

Client computing devices 1104, 1106, and 1108 may be devices similar tothose described above for 1002, 1004, 1006, and 1008.

Although exemplary system environment 1100 is shown with three clientcomputing devices, any number of client computing devices may besupported. Other devices such as devices with sensors, etc. may interactwith cloud infrastructure system 1102.

Network(s) 1110 may facilitate communications and exchange of databetween clients 1104, 1106, and 1108 and cloud infrastructure system1102. Each network may be any type of network familiar to those skilledin the art that can support data communications using any of a varietyof commercially-available protocols, including those described above fornetwork(s) 610.

Cloud infrastructure system 1102 may comprise one or more computersand/or servers that may include those described above for server 1012.

In certain embodiments, services provided by the cloud infrastructuresystem may include a host of services that are made available to usersof the cloud infrastructure system on demand, such as online datastorage and backup solutions, Web-based e-mail services, hosted officesuites and document collaboration services, database processing, managedtechnical support services, and the like. Services provided by the cloudinfrastructure system can dynamically scale to meet the needs of itsusers. A specific instantiation of a service provided by cloudinfrastructure system is referred to herein as a “service instance.” Ingeneral, any service made available to a user via a communicationnetwork, such as the Internet, from a cloud service provider's system isreferred to as a “cloud service.” Typically, in a public cloudenvironment, servers and systems that make up the cloud serviceprovider's system are different from the customer's own on-premisesservers and systems. For example, a cloud service provider's system mayhost an application, and a user may, via a communication network such asthe Internet, on demand, order and use the application.

In some examples, a service in a computer network cloud infrastructuremay include protected computer network access to storage, a hosteddatabase, a hosted web server, a software application, or other serviceprovided by a cloud vendor to a user, or as otherwise known in the art.For example, a service can include password-protected access to remotestorage on the cloud through the Internet. As another example, a servicecan include a web service-based hosted relational database and ascript-language middleware engine for private use by a networkeddeveloper. As another example, a service can include access to an emailsoftware application hosted on a cloud vendor's web site.

In certain embodiments, cloud infrastructure system 1102 may include asuite of applications, middleware, and database service offerings thatare delivered to a customer in a self-service, subscription-based,elastically scalable, reliable, highly available, and secure manner. Anexample of such a cloud infrastructure system is the Oracle Public Cloudprovided by the present assignee.

‘Big data’ can be hosted and/or manipulated by the infrastructure systemon many levels and at different scales. Extremely large data sets can bestored and manipulated by analysts and researchers to visualize largeamounts of data, detect trends, and/or otherwise interact with the data.Tens, hundreds, or thousands of processors linked in parallel can actupon such data in order to present it or simulate external forces on thedata or what it represents. These data sets can involve structured data,such as that organized in a database or otherwise according to astructured model, and/or unstructured data (e.g., emails, images, datablobs (binary large objects), web pages, complex event processing). Byleveraging an ability of an embodiment to relatively quickly focus more(or fewer) computing resources upon an objective, the cloudinfrastructure system may be better available to carry out tasks onlarge data sets based on demand from a business, government agency,research organization, private individual, group of like-mindedindividuals or organizations, or other entity.

In various embodiments, cloud infrastructure system 1102 may be adaptedto automatically provision, manage and track a customer's subscriptionto services offered by cloud infrastructure system 1102. Cloudinfrastructure system 1102 may provide the cloud services via differentdeployment models. For example, services may be provided under a publiccloud model in which cloud infrastructure system 1102 is owned by anorganization selling cloud services (e.g., owned by Oracle) and theservices are made available to the general public or different industryenterprises. As another example, services may be provided under aprivate cloud model in which cloud infrastructure system 1102 isoperated solely for a single organization and may provide services forone or more entities within the organization. The cloud services mayalso be provided under a community cloud model in which cloudinfrastructure system 1102 and the services provided by cloudinfrastructure system 1102 are shared by several organizations in arelated community. The cloud services may also be provided under ahybrid cloud model, which is a combination of two or more differentmodels.

In some embodiments, the services provided by cloud infrastructuresystem 1102 may include one or more services provided under Software asa Service (SaaS) category, Platform as a Service (PaaS) category,Infrastructure as a Service (IaaS) category, or other categories ofservices including hybrid services. A customer, via a subscriptionorder, may order one or more services provided by cloud infrastructuresystem 1102. Cloud infrastructure system 1102 then performs processingto provide the services in the customer's subscription order.

In some embodiments, the services provided by cloud infrastructuresystem 1102 may include, without limitation, application services,platform services and infrastructure services. In some examples,application services may be provided by the cloud infrastructure systemvia a SaaS platform. The SaaS platform may be configured to providecloud services that fall under the SaaS category. For example, the SaaSplatform may provide capabilities to build and deliver a suite ofon-demand applications on an integrated development and deploymentplatform. The SaaS platform may manage and control the underlyingsoftware and infrastructure for providing the SaaS services. Byutilizing the services provided by the SaaS platform, customers canutilize applications executing on the cloud infrastructure system.Customers can acquire the application services without the need forcustomers to purchase separate licenses and support. Various differentSaaS services may be provided. Examples include, without limitation,services that provide solutions for sales performance management,enterprise integration, and business flexibility for largeorganizations.

In some embodiments, platform services may be provided by the cloudinfrastructure system via a PaaS platform. The PaaS platform may beconfigured to provide cloud services that fall under the PaaS category.Examples of platform services may include without limitation servicesthat enable organizations (such as Oracle) to consolidate existingapplications on a shared, common architecture, as well as the ability tobuild new applications that leverage the shared services provided by theplatform. The PaaS platform may manage and control the underlyingsoftware and infrastructure for providing the PaaS services. Customerscan acquire the PaaS services provided by the cloud infrastructuresystem without the need for customers to purchase separate licenses andsupport. Examples of platform services include, without limitation,Oracle Java Cloud Service (JCS), Oracle Database Cloud Service (DBCS),and others.

By utilizing the services provided by the PaaS platform, customers canemploy programming languages and tools supported by the cloudinfrastructure system and also control the deployed services. In someembodiments, platform services provided by the cloud infrastructuresystem may include database cloud services, middleware cloud services(e.g., Oracle Fusion Middleware services), and Java cloud services. Inone embodiment, database cloud services may support shared servicedeployment models that enable organizations to pool database resourcesand offer customers a Database as a Service in the form of a databasecloud. Middleware cloud services may provide a platform for customers todevelop and deploy various business applications, and Java cloudservices may provide a platform for customers to deploy Javaapplications, in the cloud infrastructure system.

Various different infrastructure services may be provided by an IaaSplatform in the cloud infrastructure system. The infrastructure servicesfacilitate the management and control of the underlying computingresources, such as storage, networks, and other fundamental computingresources for customers utilizing services provided by the SaaS platformand the PaaS platform.

In certain embodiments, cloud infrastructure system 1102 may alsoinclude infrastructure resources 1130 for providing the resources usedto provide various services to customers of the cloud infrastructuresystem. In one embodiment, infrastructure resources 1130 may includepre-integrated and optimized combinations of hardware, such as servers,storage, and networking resources to execute the services provided bythe PaaS platform and the SaaS platform.

In some embodiments, resources in cloud infrastructure system 1102 maybe shared by multiple users and dynamically re-allocated per demand.Additionally, resources may be allocated to users in different timezones. For example, cloud infrastructure system 1130 may enable a firstset of users in a first time zone to utilize resources of the cloudinfrastructure system for a specified number of hours and then enablethe re-allocation of the same resources to another set of users locatedin a different time zone, thereby maximizing the utilization ofresources.

In certain embodiments, a number of internal shared services 1132 may beprovided that are shared by different components or modules of cloudinfrastructure system 1102 and by the services provided by cloudinfrastructure system 1102. These internal shared services may include,without limitation, a security and identity service, an integrationservice, an enterprise repository service, an enterprise managerservice, a virus scanning and white list service, a high availability,backup and recovery service, service for enabling cloud support, anemail service, a notification service, a file transfer service, and thelike.

In certain embodiments, cloud infrastructure system 1102 may providecomprehensive management of cloud services (e.g., SaaS, PaaS, and IaaSservices) in the cloud infrastructure system. In one embodiment, cloudmanagement functionality may include capabilities for provisioning,managing and tracking a customer's subscription received by cloudinfrastructure system 1102, and the like.

In one embodiment, as depicted in the figure, cloud managementfunctionality may be provided by one or more modules, such as an ordermanagement module 1120, an order orchestration module 1122, an orderprovisioning module 1124, an order management and monitoring module1126, and an identity management module 1128. These modules may includeor be provided using one or more computers and/or servers, which may begeneral purpose computers, specialized server computers, server farms,server clusters, or any other appropriate arrangement and/orcombination.

In exemplary operation 1134, a customer using a client device, such asclient device 1104, 1106 or 1108, may interact with cloud infrastructuresystem 1102 by requesting one or more services provided by cloudinfrastructure system 1102 and placing an order for a subscription forone or more services offered by cloud infrastructure system 1102. Incertain embodiments, the customer may access a cloud User Interface(UI), cloud UI 1112, cloud UI 1114 and/or cloud UI 1116 and place asubscription order via these UIs. The order information received bycloud infrastructure system 1102 in response to the customer placing anorder may include information identifying the customer and one or moreservices offered by the cloud infrastructure system 1102 that thecustomer intends to subscribe to.

After an order has been placed by the customer, the order information isreceived via the cloud UIs, 1112, 1114 and/or 1116.

At operation 1136, the order is stored in order database 1118. Orderdatabase 1118 can be one of several databases operated by cloudinfrastructure system 1118 and operated in conjunction with other systemelements.

At operation 1138, the order information is forwarded to an ordermanagement module 1120. In some instances, order management module 1120may be configured to perform billing and accounting functions related tothe order, such as verifying the order, and upon verification, bookingthe order.

At operation 1140, information regarding the order is communicated to anorder orchestration module 1122. Order orchestration module 1122 mayutilize the order information to orchestrate the provisioning ofservices and resources for the order placed by the customer. In someinstances, order orchestration module 1122 may orchestrate theprovisioning of resources to support the subscribed services using theservices of order provisioning module 1124.

In certain embodiments, order orchestration module 1122 enables themanagement of business processes associated with each order and appliesbusiness logic to determine whether an order should proceed toprovisioning. At operation 1142, upon receiving an order for a newsubscription, order orchestration module 1122 sends a request to orderprovisioning module 1124 to allocate resources and configure thoseresources needed to fulfill the subscription order. Order provisioningmodule 1124 enables the allocation of resources for the services orderedby the customer. Order provisioning module 1124 provides a level ofabstraction between the cloud services provided by cloud infrastructuresystem 1100 and the physical implementation layer that is used toprovision the resources for providing the requested services. Orderorchestration module 1122 may thus be isolated from implementationdetails, such as whether or not services and resources are actuallyprovisioned on the fly or pre-provisioned and only allocated/assignedupon request.

At operation 1144, once the services and resources are provisioned, anotification of the provided service may be sent to customers on clientdevices 1104, 1106 and/or 1108 by order provisioning module 1124 ofcloud infrastructure system 1102.

At operation 1146, the customer's subscription order may be managed andtracked by an order management and monitoring module 1126. In someinstances, order management and monitoring module 1126 may be configuredto collect usage statistics for the services in the subscription order,such as the amount of storage used, the amount data transferred, thenumber of users, and the amount of system up time and system down time.

In certain embodiments, cloud infrastructure system 1100 may include anidentity management module 1128. Identity management module 1128 may beconfigured to provide identity services, such as access management andauthorization services in cloud infrastructure system 1100. In someembodiments, identity management module 1128 may control informationabout customers who wish to utilize the services provided by cloudinfrastructure system 1102. Such information can include informationthat authenticates the identities of such customers and information thatdescribes which actions those customers are authorized to performrelative to various system resources (e.g., files, directories,applications, communication ports, memory segments, etc.) Identitymanagement module 1128 may also include the management of descriptiveinformation about each customer and about how and by whom thatdescriptive information can be accessed and modified.

FIG. 12 illustrates an exemplary computer system 1200, in which variousembodiments of the present disclosure may be implemented. The system1200 may be used to implement any of the computer systems describedabove. As shown in the figure, computer system 1200 includes aprocessing unit 1204 that communicates with a number of peripheralsubsystems via a bus subsystem 1202. These peripheral subsystems mayinclude a processing acceleration unit 1206, an I/O subsystem 1208, astorage subsystem 1218 and a communications subsystem 1224. Storagesubsystem 1218 includes tangible computer-readable storage media 1222and a system memory 1210.

Bus subsystem 1202 provides a mechanism for letting the variouscomponents and subsystems of computer system 1200 communicate with eachother as intended. Although bus subsystem 1202 is shown schematically asa single bus, alternative embodiments of the bus subsystem may utilizemultiple buses. Bus subsystem 1202 may be any of several types of busstructures including a memory bus or memory controller, a peripheralbus, and a local bus using any of a variety of bus architectures. Forexample, such architectures may include an Industry StandardArchitecture (ISA) bus, Micro Channel Architecture (MCA) bus, EnhancedISA (EISA) bus, Video Electronics Standards Association (VESA) localbus, and Peripheral Component Interconnect (PCI) bus, which can beimplemented as a Mezzanine bus manufactured to the IEEE P1386.1standard.

Processing unit 1204, which can be implemented as one or more integratedcircuits (e.g., a conventional microprocessor or microcontroller),controls the operation of computer system 1200. One or more processorsmay be included in processing unit 1204. These processors may includesingle core or multicore processors. In certain embodiments, processingunit 1204 may be implemented as one or more independent processing units1232 and/or 1234 with single or multicore processors included in eachprocessing unit. In other embodiments, processing unit 1204 may also beimplemented as a quad-core processing unit formed by integrating twodual-core processors into a single chip.

In various embodiments, processing unit 1204 can execute a variety ofprograms in response to program code and can maintain multipleconcurrently executing programs or processes. At any given time, some orall of the program code to be executed can be resident in processor(s)1204 and/or in storage subsystem 1218. Through suitable programming,processor(s) 1204 can provide various functionalities described above.Computer system 1200 may additionally include a processing accelerationunit 1206, which can include a digital signal processor (DSP), aspecial-purpose processor, and/or the like.

I/O subsystem 1208 may include user interface input devices and userinterface output devices. User interface input devices may include akeyboard, pointing devices such as a mouse or trackball, a touchpad ortouch screen incorporated into a display, a scroll wheel, a click wheel,a dial, a button, a switch, a keypad, audio input devices with voicecommand recognition systems, microphones, and other types of inputdevices. User interface input devices may include, for example, motionsensing and/or gesture recognition devices such as the Microsoft Kinect®motion sensor that enables users to control and interact with an inputdevice, such as the Microsoft Xbox® 360 game controller, through anatural user interface using gestures and spoken commands. Userinterface input devices may also include eye gesture recognition devicessuch as the Google Glass® blink detector that detects eye activity(e.g., ‘blinking’ while taking pictures and/or making a menu selection)from users and transforms the eye gestures as input into an input device(e.g., Google Glass®). Additionally, user interface input devices mayinclude voice recognition sensing devices that enable users to interactwith voice recognition systems (e.g., Siri® navigator), through voicecommands.

User interface input devices may also include, without limitation, threedimensional (3D) mice, joysticks or pointing sticks, gamepads andgraphic tablets, and audio/visual devices such as speakers, digitalcameras, digital camcorders, portable media players, webcams, imagescanners, fingerprint scanners, barcode reader 3D scanners, 3D printers,laser rangefinders, and eye gaze tracking devices. Additionally, userinterface input devices may include, for example, medical imaging inputdevices such as computed tomography, magnetic resonance imaging,position emission tomography, medical ultrasonography devices. Userinterface input devices may also include, for example, audio inputdevices such as MIDI keyboards, digital musical instruments and thelike.

User interface output devices may include a display subsystem, indicatorlights, or non-visual displays such as audio output devices, etc. Thedisplay subsystem may be a cathode ray tube (CRT), a flat-panel device,such as that using a liquid crystal display (LCD) or plasma display, aprojection device, a touch screen, and the like. In general, use of theterm “output device” is intended to include all possible types ofdevices and mechanisms for outputting information from computer system1200 to a user or other computer. For example, user interface outputdevices may include, without limitation, a variety of display devicesthat visually convey text, graphics and audio/video information such asmonitors, printers, speakers, headphones, automotive navigation systems,plotters, voice output devices, and modems.

Computer system 1200 may comprise a storage subsystem 1218 thatcomprises software elements, shown as being currently located within asystem memory 1210. System memory 1210 may store program instructionsthat are loadable and executable on processing unit 1204, as well asdata generated during the execution of these programs.

Depending on the configuration and type of computer system 1200, systemmemory 1210 may be volatile (such as random access memory (RAM)) and/ornon-volatile (such as read-only memory (ROM), flash memory, etc.) TheRAM typically contains data and/or program modules that are immediatelyaccessible to and/or presently being operated and executed by processingunit 1204. In some implementations, system memory 1210 may includemultiple different types of memory, such as static random access memory(SRAM) or dynamic random access memory (DRAM). In some implementations,a basic input/output system (BIOS), containing the basic routines thathelp to transfer information between elements within computer system1200, such as during start-up, may typically be stored in the ROM. Byway of example, and not limitation, system memory 1210 also illustratesapplication programs 1212, which may include client applications, Webbrowsers, mid-tier applications, relational database management systems(RDBMS), etc., program data 1214, and an operating system 1216. By wayof example, operating system 1216 may include various versions ofMicrosoft Windows®, Apple Macintosh®, and/or Linux operating systems, avariety of commercially-available UNIX® or UNIX-like operating systems(including without limitation the variety of GNU/Linux operatingsystems, the Google Chrome® OS, and the like) and/or mobile operatingsystems such as iOS, Windows® Phone, Android® OS, BlackBerry® 12 OS, andPalm® OS operating systems.

Storage subsystem 1218 may also provide a tangible computer-readablestorage medium for storing the basic programming and data constructsthat provide the functionality of some embodiments. Software (programs,code modules, instructions) that when executed by a processor providethe functionality described above may be stored in storage subsystem1218. These software modules or instructions may be executed byprocessing unit 1204. Storage subsystem 1218 may also provide arepository for storing data used in accordance with the presentdisclosure.

Storage subsystem 1200 may also include a computer-readable storagemedia reader 1220 that can further be connected to computer-readablestorage media 1222. Together and, optionally, in combination with systemmemory 1210, computer-readable storage media 1222 may comprehensivelyrepresent remote, local, fixed, and/or removable storage devices plusstorage media for temporarily and/or more permanently containing,storing, transmitting, and retrieving computer-readable information.

Computer-readable storage media 1222 containing code, or portions ofcode, can also include any appropriate media known or used in the art,including storage media and communication media, such as but not limitedto, volatile and non-volatile, removable and non-removable mediaimplemented in any method or technology for storage and/or transmissionof information. This can include tangible, non-transitorycomputer-readable storage media such as RAM, ROM, electronicallyerasable programmable ROM (EEPROM), flash memory or other memorytechnology, CD-ROM, digital versatile disk (DVD), or other opticalstorage, magnetic cassettes, magnetic tape, magnetic disk storage orother magnetic storage devices, or other tangible computer readablemedia. When specified, this can also include nontangible, transitorycomputer-readable media, such as data signals, data transmissions, orany other medium which can be used to transmit the desired informationand which can be accessed by computing system 1200.

By way of example, computer-readable storage media 1222 may include ahard disk drive that reads from or writes to non-removable, nonvolatilemagnetic media, a magnetic disk drive that reads from or writes to aremovable, nonvolatile magnetic disk, and an optical disk drive thatreads from or writes to a removable, nonvolatile optical disk such as aCD ROM, DVD, and Blu-Ray® disk, or other optical media.Computer-readable storage media 1222 may include, but is not limited to,Zip® drives, flash memory cards, universal serial bus (USB) flashdrives, secure digital (SD) cards, DVD disks, digital video tape, andthe like. Computer-readable storage media 1222 may also include,solid-state drives (SSD) based on non-volatile memory such asflash-memory based SSDs, enterprise flash drives, solid state ROM, andthe like, SSDs based on volatile memory such as solid state RAM, dynamicRAM, static RAM, DRAM-based SSDs, magnetoresistive RAM (MRAM) SSDs, andhybrid SSDs that use a combination of DRAM and flash memory based SSDs.The disk drives and their associated computer-readable media may providenon-volatile storage of computer-readable instructions, data structures,program modules, and other data for computer system 1200.

Communications subsystem 1224 provides an interface to other computersystems and networks. Communications subsystem 1224 serves as aninterface for receiving data from and transmitting data to other systemsfrom computer system 1200. For example, communications subsystem 1224may enable computer system 1200 to connect to one or more devices viathe Internet. In some embodiments communications subsystem 1224 caninclude radio frequency (RF) transceiver components for accessingwireless voice and/or data networks (e.g., using cellular telephonetechnology, advanced data network technology, such as 3G, 4G or EDGE(enhanced data rates for global evolution), WiFi (IEEE 602.11 familystandards, or other mobile communication technologies, or anycombination thereof), global positioning system (GPS) receivercomponents, and/or other components. In some embodiments communicationssubsystem 1224 can provide wired network connectivity (e.g., Ethernet)in addition to or instead of a wireless interface.

In some embodiments, communications subsystem 1224 may also receiveinput communication in the form of structured and/or unstructured datafeeds 1226, event streams 1228, event updates 1230, and the like onbehalf of one or more users who may use computer system 1200.

By way of example, communications subsystem 1224 may be configured toreceive data feeds 1226 in real-time from users of social media networksand/or other communication services such as Twitter® feeds, Facebook®updates, web feeds such as Rich Site Summary (RSS) feeds, and/orreal-time updates from one or more third party information sources.

Additionally, communications subsystem 1224 may also be configured toreceive data in the form of continuous data streams, which may includeevent streams 1228 of real-time events and/or event updates 1230, thatmay be continuous or unbounded in nature with no explicit end. Examplesof applications that generate continuous data may include, for example,sensor data applications, financial tickers, network performancemeasuring tools (e.g. network monitoring and traffic managementapplications), clickstream analysis tools, automobile trafficmonitoring, and the like.

Communications subsystem 1224 may also be configured to output thestructured and/or unstructured data feeds 1226, event streams 1228,event updates 1230, and the like to one or more databases that may be incommunication with one or more streaming data source computers coupledto computer system 1200.

Computer system 1200 can be one of various types, including a handheldportable device (e.g., an iPhone® cellular phone, an iPad® computingtablet, a PDA), a wearable device (e.g., a Google Glass® head mounteddisplay), a PC, a workstation, a mainframe, a kiosk, a server rack, orany other data processing system.

Due to the ever-changing nature of computers and networks, thedescription of computer system 1200 depicted in the figure is intendedonly as a specific example. Many other configurations having more orfewer components than the system depicted in the figure are possible.For example, customized hardware might also be used and/or particularelements might be implemented in hardware, firmware, software (includingapplets), or a combination. Further, connection to other computingdevices, such as network input/output devices, may be employed. Based onthe disclosure and teachings provided herein, a person of ordinary skillin the art will appreciate other ways and/or methods to implement thevarious embodiments.

In the foregoing specification, aspects of the disclosure are describedwith reference to specific embodiments thereof, but those skilled in theart will recognize that the disclosure is not limited thereto. Variousfeatures and aspects of the above-described disclosure may be usedindividually or jointly. Further, embodiments can be utilized in anynumber of environments and applications beyond those described hereinwithout departing from the broader spirit and scope of thespecification. The specification and drawings are, accordingly, to beregarded as illustrative rather than restrictive.

What is claimed is:
 1. A method, comprising: defining a polygoncomprising an affected area on a map; receiving first event datacomprising position information for an entity located at a physicallocation represented by the map; determining a level of detail forprocessing second event data; adjusting the polygon based at least inpart on the first level of detail; joining the first event data withadjusted polygon information that corresponds to the adjusted polygon;identifying whether the entity is within the affected area based atleast in part on a determination of whether the position informationcorresponds to the adjusted polygon information; preparing a userinterface for presenting a visualization configured to illustratewhether the entity is within the affected area; and providing the userinterface for presentation of the map.
 2. The method of claim 1, whereinthe level of detail is determined based at least in part on contextinformation associated with the map or the entity, and wherein thecontext information comprises a proximity parameter with a directmathematical relationship to a relative proximity of the entity with theaffected area.
 3. The method of claim 2, wherein the level of detail isdecreased as the proximity parameter increases, and wherein the level ofdetail is increased as the proximity parameter decreases.
 4. The methodof claim 2, wherein the context information comprises a complexityparameter with a direct mathematical relationship to a relativecomplexity of a shape of the polygon.
 5. The method of claim 4, whereinthe level of detail is decreased as the complexity parameter increases,and wherein the level of detail is increased as the complexity parameterdecreases.
 6. The method of claim 5, wherein adjusting the polygoncomprises decreasing a number of points of the polygon when the level ofdetail is decreased or increasing the number of points when the level ofdetail is increased.
 7. The method of claim 1, wherein the second eventdata comprises location information, and wherein the locationinformation comprises at least one of a geographic attribute or aspatial attribute.
 8. The method of claim 1, further comprisingdetermining a second level of detail for visualizing whether the entityis within the affected area based at least in part on a zoom level ofthe map.
 9. The method of claim 8, wherein the user interface isprepared based at least in part on the second level of detail.
 10. Acomputer-readable medium storing computer-executable instructions that,when executed by one or more processors, configures one or more computersystems to perform operations comprising: defining a polygon comprisingan affected area on a map; receiving first event data comprisingposition information for an entity located at a physical locationrepresented by the map; determining a level of detail for processingsecond event data; adjusting the polygon based at least in part on thefirst level of detail; joining the first event data with adjustedpolygon information that corresponds to the adjusted polygon;identifying whether the entity is within the affected area based atleast in part on a determination of whether the position informationcorresponds to the adjusted polygon information; preparing a userinterface for presenting a visualization configured to illustratewhether the entity is within the affected area; and providing the userinterface for presentation of the map.
 11. The computer-readable mediumof claim 9, wherein the operations further comprise determining a secondlevel of detail for visualizing whether the entity is within theaffected area based at least in part on a zoom level of the map.
 12. Thecomputer-readable medium of claim 9, wherein the polygon defines ageofence.
 13. The computer-readable medium of claim 12, wherein theoperations further comprise determining whether the object is within adistance of the geofence prior to identifying whether the object iswithin the affected area.
 14. The computer-readable medium of claim 9,wherein the second event data comprises weather information.
 15. Asystem, comprising: a memory storing a plurality of instructions; and aprocessor configured to access the memory, the processor furtherconfigured to execute the plurality of instructions to at least:defining a polygon comprising an affected area on a map; receiving firstevent data comprising position information for an object; determining alevel of detail for processing second event data; adjusting the polygonbased at least in part on the first level of detail; joining the firstevent data with adjusted polygon information that corresponds to theadjusted polygon; identifying whether the object is within the affectedarea based at least in part on a determination of whether the positioninformation corresponds to the adjusted polygon information; preparing auser interface for presenting a visualization configured to illustratewhether the object is within the affected area; and providing the userinterface for presentation of the map.
 16. The system of claim 15,wherein the polygon is stored in a spatial index.
 17. The system ofclaim 16, wherein the second event data is identified by queryingagainst the spatial index.
 18. The system of claim 15, wherein thepolygon is an approximation of the second event data.
 19. The system ofclaim 15, wherein the object comprises a computing device on a vehiclemoving at a physical location corresponding to the map.
 20. The systemof claim 15, wherein the level of detail is determined based at least inpart on context information associated with the map or the entity, andwherein the context information comprises a relative complexity of thepolygon, and wherein a number of points of the polygon are reduced whenthe relative complexity of the polygon is above a threshold.